Questions tagged [survival]
Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.
3,569 questions
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How to handle calendar year as a continuous predictor with a mismatched train/test time horizon?
I am using Ordinal Semiparametric Regression (Frank Harrell's rms package) to model overall survival in patients with brain tumor.
My training data is from the SEER database (covering years 2004 to ...
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Is GVIF meaningful for a reduced interaction block created from manually coded factor × treatment terms?
I’m fitting a survival model with a multi-level factor (HistologyClass) and binary treatment variables (Radiotherapy, Chemotherapy). I do not want the full HistologyClass * Treatment interaction, ...
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Survival proportion for censored data
Let's consider the below example as a life table for survival analysis:
At time 124, we have censored patinet, lost to follow up.
Generally, I have noticed that we don't get from the software ...
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Markov State Transition Models vs the Win Ratio in clinical trials
I have recently become interested in Markov State Transition Models for the analysis of clinical trials with composite endpoints, such as the Markov Longitudinal Ordinal Model described in Frank ...
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C-Index less than 0.5 for NNnPH Survival Model
I am working with Neural Network violating Proportional Hazard survival model. This model directly incorporates the proportional hazard into its architecture.
I have applied this model in UnempDur ...
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How does the Cox hazard regression model change with a main vs. interactive model?
How do these two differ in terms of interpretation? When should one be used over the other?
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How should I compare two survival prediction models when a predictor’s definition drifts over time?
I am comparing two survival prediction models for CNS tumor patients, and my main concern is temporal drift in histology definitions rather than ordinary overfitting.
My development dataset is SEER (...
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Survival analysis options for nested cancer data
I commonly work with cancer data that is on the patient-lesion level, as patients with metastases often have multiple treated lesions. While looking at patient survival is easy, I get a bit stuck with ...
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Are my simulations of multi-level survival times correct?
I came across the article from Bender et al.(2005) and attempted to put this into R code to simulate survival times based on an empirical baseline hazard from existing data.
I compute survival times ...
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Kaplan Meier method for integrated brier score calculation in python [closed]
I have done 5 fold cross validation to create 5 fold: three for training data, one for validation and one for test data. I want to perform Kaplan-Meier method in this data.
I have computed 10 unique ...
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Application of step function for time dependent covariates in coxme?
In one of my dissertation chapters, I am using survival analysis to assess time to next birth following calf loss in a wild dolphin population to address costs to female fitness. My question is about ...
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Understanding PH Assumption for Cause-Specific Hazard Model
I am trying to understand the Cox PH assumption when using a Cause-Specific Hazard Model. I have a dataset of 5,000 observations, split 50/50 between treatment and placebo. There is a main event of ...
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Pseudo R-squared in the time-dependent Cox PH model
(Maybe the follow-up of this post: Running Cox PH model with time-dependent variables using large data)
I used Case-Cohort subsampling to fit the Cox proportional hazard model with time-dependent ...
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Pre-processing of longitudinal data to convert to a regular survival analysis
I am working on a benchmark study of survival models and that is why, I am working with a wider array of survival datasets. In my repository, I have 50 survival datasets including regular events and ...
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The difference in VIF between frailty model and standard Cox model with robust estimator
I am analyzing multicenter datasets using both frailty models and standard Cox models with robust standard errors.
For each dataset, the VIF (calculated via rms::vif()) in the frailty models is very ...
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